Theoretical Neuroscience Course Part I (2006)

General course information is here.

The teaching schedule is as follows.
Lecturesevery Tuesday and Friday, 11 am - 1 pm, from 3 October to 12 December
Review Sessionsevery Friday, 1 pm - 2 pm
VenueGatsby Unit room 409, 4th floor
Alexandra House, 17 Queen Square
London WC1N 3AR
The main course book is Theoretical Neuroscience by Dayan and Abbott. The appendix of the book describes the maths needed for the course. If you need to brush up on mathematics, one recommended book is Riley, Hobson and Bence: Mathematical Methods for Physicists. For a very simple intro to first order ODE's, see Hugh Wilson: spikes, decisions and actions, chapters 1 and 2. A few very useful cribsheets are basic maths you'll need for this course, and some matrix identities. You might also be interested in the Gatsby neuroscience journal club.
Below is a schedule of the review sessions (updated before every review session). The homework assignments can be downloaded from here. The section "reading" lists background reading material and is (usually) not meant as compulsory.
Date ReadingAssignment
13-10review session 1
Hodgkin & Huxley etc
Dayan and Abbott, chapter 5
Hodgkin & Huxley, '52 (the pioneering paper on channel modeling)
lecture slides
homework 1
27-10review session 2
cable equation, synapses
Dayan and Abbott, chapter 6
for the keen: Koch (1999) ch. 2-5
homework 2
03-11review session 3
neural encoding
lecture slides (1)
lecture slides (2)
Dayan and Abbott, chapters 1-2
homework 3
10-11review session 4
neural decoding
lecture slides
Dayan and Abbott, chapter 3
Population codes
homework 4
17-11review session 5
information theory
Dayan and Abbott, chapter 4
lecture slides
homework 5
24-11review session 6
Dayan and Abbott, chapter 7 homework 6
01-12review session 7
dynamics and vision
Dayan and Abbott, chapter 7
Theoretical understanding of the early visual processes
homework 7
08-12review session 8
Hebbian learning and vision
Dayan and Abbott, chapter 8
lecture slides 1 (Hebbian learning)
lecture slides 2 (vision)
lecture slides 3 (vision)
homework 8
15-12review session 9
reinforcement learning
Dayan and Abbott, chapter 9
lecture slides (1)
lecture slides (2)
homework 9